Normative industrial symbiotic networks: a position paper

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2 Citations (Scopus)

Abstract

In this paper, we introduce a normative, multi-agent perspective on the field of industrial symbiosis research and propose normative institutions as a key technology for operating Industrial Symbiotic Networks (ISNs), both as a framework to represent and reason about dynamic behaviour of ISNs and as a platform for design and maintenance of such networks. We discuss the requirements of normative agent-based frameworks for ISNs with respect to agent interactions, joint commitments, and the organisation to monitor interactions in ISNs.
Original languageEnglish
Title of host publicationMulti-agent systems and agreement technologies
Subtitle of host publication14th European Conference, EUMAS 2016, and 4th International Conference, AT 2016, Valencia, Spain, December 15-16, 2016, Revised Selected Papers
EditorsN. Criado Pacheco, C. Carrascosa, N. Osman, V. Julián Inglada
PublisherSpringer
Pages314-321
Number of pages8
ISBN (Electronic)978-3-319-59294-7
ISBN (Print)978-3-319-59293-0
DOIs
Publication statusPublished - 23 Jun 2017
Event14th European Conference on Multi-Agent Systems, EUMAS 2016 - Valencia, Spain
Duration: 15 Dec 201616 Dec 2016
Conference number: 4

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10207
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence
PublisherSpringer

Conference

Conference14th European Conference on Multi-Agent Systems, EUMAS 2016
Abbreviated titleEUMAS
CountrySpain
CityValencia
Period15/12/1616/12/16

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    Yazdanpanah, V., Yazan, D. M., & Zijm, W. H. M. (2017). Normative industrial symbiotic networks: a position paper. In N. Criado Pacheco, C. Carrascosa, N. Osman, & V. Julián Inglada (Eds.), Multi-agent systems and agreement technologies: 14th European Conference, EUMAS 2016, and 4th International Conference, AT 2016, Valencia, Spain, December 15-16, 2016, Revised Selected Papers (pp. 314-321). (Lecture Notes in Computer Science; Vol. 10207), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-319-59294-7